Online software Boneureka assessing bone age based on metacarpal length in healthy children: proof-of-concept study.

BACKGROUND: Bone age in children is mainly assessed using the Greulich and Pyle (GP) atlas, a validated method with limited interobserver accuracy. While automated methods increase interobserver accuracy, they represent considerable costs and technical requirements. OBJECTIVE: A proof-of-concept study to create and evaluate an online software program, Boneureka©, based on linear metacarpal length measurements, to assess bone age in healthy children. MATERIALS AND METHODS: The study retrospectively included 434 consecutive children (215 girls) who underwent a left-hand radiograph to rule out trauma between March 2008 and December 2017. Two reviewers measured the second to fourth metacarpal lengths on each radiograph and the distance between the centre of the epiphyses of the second and fifth metacarpals. A single reviewer estimated the bone age using the GP atlas. The automated software assessed the bone age for all radiographs. A mathematical model was developed based on linear regressions to provide the mean bone age and standard deviation based on the estimates. Pearson and intraclass correlation coefficient (ICC) were used to evaluate the correlation and agreement between the estimated bone ages using Boneureka©, the GP atlas and BoneXpert® compared to chronological age. RESULTS: The measure that showed the highest correlation (r2=0.877 for girls and r2=0.834 for boys; P<.001) and the highest ICC (ICC=0.937 for girls and ICC=0.926 for boys; P<0.001) with chronological age was length of the second metacarpal. The GP atlas and the automated software evaluation had excellent ICC with chronological age (ICC>0.95 for both methods and sexes). Using this data, we created an online software program based on the second metacarpal length to obtain bone age estimates, means and standard deviations. CONCLUSION: The newly created online software Boneureka,© based on the second metacarpal length, is a reliable and user-friendly tool to assess bone age in healthy children. Further studies on a larger population should be performed to validate the developed reference values.

A stroke mimic with left-hemispheric leptomeningeal vessel paucity and hypoperfusion.

In the neuroimaging workup of a suspected ischemic stroke, the involvement of more than one arterial territory without an anatomical substrate should raise the suspicion of a stroke mimic. We report the case of a 61-year-old male with a new-onset headache and transient phasic disturbances who presented a pattern of vascular abnormalities characterized by left-hemispheric leptomeningeal vessel paucity and hypoperfusion.

Endovascular NBCA treatment of a ruptured arteriovenous malformation with venous pseudoaneurysm in a young child.

We reported imaging findings of arterio-venous malformation complicated by hemorrhage and venous pseudoaneurysm in a young child consulting for headache and emesis: to our knowledge venous pseudoaneurysm in association with ruptured arteriovenous malformation is a rare complication reported in the literature. We present the indications for endovascular treatment, especially with NBCA (N-butyl cyanoacrylate).

Chest CT scan predictors of intensive care unit admission in hospitalized pregnant women with COVID-19: a case-control study.

PURPOSE: To investigate the role of chest computed tomography (CT) scan in the prediction of admission of pregnant women with COVID-19 into intensive care unit (ICU). METHODS: This was a single-center retrospective case-control study. We included pregnant women diagnosed with COVID-19 by reverse transcriptase polymerase chain reaction between February 2020 and July 2021, requiring hospital admission due to symptoms, who also had a CT chest scan at presentation. Patients admitted to the ICU (case group) were compared with patients who did not require ICU admission (control group). The CT scans were reported by an experienced radiologist, blinded to the patient's course and outcome, aided by an artificial intelligence software. Total CT scan score, chest CT severity score (CT-SS), total lung volume (TLV), infected lung volume (ILV), and infected-to-total lung volume ratio (ILV/TLV) were calculated. Receiver operating characteristic curves were constructed to test the sensitivity and specificity of each parameter. RESULTS: 8/28 patients (28.6%) required ICU admission. These also had lower TLV, higher ILV, and ILV/TLV. The area under the curve (AUC) for these three parameters was 0.789, 0.775, and 0.763, respectively. TLV, ILV, and ILV/TLV had good sensitivity (62.5%, 87.5%, and 87.5%, respectively) and specificity (84.2%, 70%, and 73.7%, respectively) for predicting ICU admission at the following selected thresholds: 2255 mL, 319 mL, and 14%, respectively. The performance of CT-SS, CT scan score, and ILV/TLV in predicting ICU admission was comparable. CONCLUSION: TLV, ILV, and ILV/TLV as measured by an artificial intelligence software on chest CT, may predict ICU admission in hospitalized pregnant women, symptomatic for COVID-19.

Interest of routine MR spectroscopic techniques for differential diagnosis between radionecrosis and progression of brain tumor lesions.

Objectives: The main objective of the study is to assess the feasibility and reproducibility of routine MRS to assist in the differential diagnosis between post-radiation necrosis and tumor progression. The secondary objective is to evaluate the accuracy of the method. Method: An additional sequence of MRS was added to the standard protocol routinely used for patient follow-up. To assess discomfort a control group was formed. The time required to perform MRS and analysis of results, and data about artefacts and technical limitations were collected. MRS results analyzed independently by two neuroradiologists were compared. The diagnostic accuracy of MRS was calculated using a composite reference standard. Results: The experimental group included 38 patients, the control group 41. The discomfort felt during the examination, is not significantly different between the groups. The average quality of SRM is rated as low. The frequency of cerebral radionecrosis is 13 % based on the reference standard used, 54 % and 46 % based on MRS results for the two observers. The additional time is 19,5 min. There is strong inter-observer agreement. The sensitivity and specificity of MRS are respectively for the diagnosis of radionecrosis of 60 % and 45 % (PPV = 16 %NPV = 87 %), for the diagnosis of tumor tissue of 25 % and 94 % (PPV = 80 %NPV = 57%). Conclusion: MRS is probably not applicable in routine clinical practice; however, in view of our results and the literature, in selected cases, it could be a support in the diagnosis of radionecrosis or brain tumor progression. Radionecrosis is probably underestimated.

Comparison of Chest Computed Tomography Between the Two Waves of Coronavirus Disease 2019 in Belgium Using Artificial Intelligence.

Background In this study, we aimed to compare two outbreaks of coronavirus disease 2019 (COVID-19) in Belgium in tomographic and biological-clinical aspects with artificial intelligence (AI). Methodology We performed an observational retrospective study. Adult patients who were symptomatic in the first seven days with COVID-19 infection, diagnosed by chest computed tomography (CT) and/or reverse transcription-polymerase chain reaction, were included in this study. The first wave of the pandemic lasted from March 25, 2020, to May 25, 2020, and the second wave lasted from October 7, 2020, to December 7, 2020. For each wave, two subgroups were defined depending on whether respiratory failure occurred during the course of the disease. The quantitative estimation of COVID-19 lung lesions was performed by AI, radiologists, and radiology residents. The chest CT severity score was calculated by AI. Results In the 202 patients included in this study, we found statistically significant differences for obesity, hypertension, and asthma. The differences were predominant in the second wave. Moreover, a mixed distribution (central and peripherical) of pulmonary lesions was noted in the second wave, but no differences were noted regarding mortality, respiratory failure, complications, and other radiological and biological elements. Chest CT severity score was among the risk factors of mortality and respiratory failure. There was a mild agreement between AI and visual evaluation of pulmonary lesion extension (K = 0.4). Conclusions Between March and December 2020, in our cohort, for the majority of the parameters analyzed, we did not record significant changes between the two waves. AI can reduce the experience and performance gap of radiologists and better establish a hospitalization criterion.